vision/src/autogluon/vision/_gluoncv/image_classification.py [89:105]:
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    final_fit = args.pop('final_fit', False)
    # train, val data
    train_data = args.pop('train_data')
    val_data = args.pop('val_data')
    # wall clock tick limit
    wall_clock_tick = args.pop('wall_clock_tick')
    log_dir = args.pop('log_dir', os.getcwd())
    # exponential batch size for Int() space batch sizes
    exp_batch_size = args.pop('exp_batch_size', False)
    if exp_batch_size and 'batch_size' in args:
        args['batch_size'] = 2 ** args['batch_size']
    try:
        task = args.pop('task')
        dataset = args.pop('dataset')
        num_trials = args.pop('num_trials')
    except KeyError:
        task = None
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vision/src/autogluon/vision/_gluoncv/object_detection.py [72:88]:
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    final_fit = args.pop('final_fit', False)
    # train, val data
    train_data = args.pop('train_data')
    val_data = args.pop('val_data')
    # wall clock tick limit
    wall_clock_tick = args.pop('wall_clock_tick')
    log_dir = args.pop('log_dir', os.getcwd())
    # exponential batch size for Int() space batch sizes
    exp_batch_size = args.pop('exp_batch_size', False)
    if exp_batch_size and 'batch_size' in args:
        args['batch_size'] = 2 ** args['batch_size']
    try:
        task = args.pop('task')
        dataset = args.pop('dataset')
        num_trials = args.pop('num_trials')
    except KeyError:
        task = None
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